User-Centric Delay-Aware Joint Caching and User Association Optimization in Cache-Enabled Wireless Networks

The mobile edge caching is a promising way to reduce the user-perceived delay and improve the transmission data rates for the wireless networks. However, the cache capacities of base stations (BSs) tend to be limited and users' interests for the contents are diverse, which makes the content pla...

Full description

Bibliographic Details
Main Authors: Wenpeng Jing, Xiangming Wen, Zhaoming Lu, Haijun Zhang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8720153/
Description
Summary:The mobile edge caching is a promising way to reduce the user-perceived delay and improve the transmission data rates for the wireless networks. However, the cache capacities of base stations (BSs) tend to be limited and users' interests for the contents are diverse, which makes the content placement decision critical for the network performance optimization. Besides, due to the flexible user-BS association, it is more complicated to optimize the content delivery and placement which are coupled with each other. This paper investigates the content placement and content delivery strategies in the cache-enabled wireless networks. In particular, the effective capacity, which can characterize the end-to-end user-perceived delay and data rates simultaneously, is introduced as the user's utility metric. As the content caching and content delivery operate in different time-scales, they are investigated separately. For the content caching, a content placement problem is formulated, where both users' different active levels and diverse content preferences are considered. Due to the NP-hard nature, the problem is decomposed into two sub-problems, and an iterative association-aware content placement algorithm is proposed. For the content delivery, the user-BS association problem is formulated, and a cache-aware user-BS association algorithm is designed. The performance of the proposed algorithms is evaluated based on the simulations. The numerical results show that the proposed algorithms have a better capability to cope with users' diverse active levels, and achieve a better performance in terms of effective capacity and fairness level, compared with the existing algorithms.
ISSN:2169-3536